2024·Journal of Lightwave Technology · 42(1)·First author·IF 4.8

End-to-end deep-learning-based photonic-assisted multi-user fiber–mmWave integrated communication system

A. Sun, et al.
Fudan University

DOI Scholar Related work
TL;DR A 6G-oriented end-to-end deep-learning framework (AMEF) for multi-user photonic-assisted fiber–mmWave integrated communications, comprising a multi-channel model (MCM) and a multi-user transceiver (MUT) with MLP-based encoder/decoder. A two-user 10 km fiber–mmWave experiment delivers 66 Gbps in the wireless-only system and 49.5 Gbps in the integrated fiber-wireless system, with >1.1 dB / >0.6 dB sensitivity gains over mCAP.
deep learningfiber-mmWavecommunication systems
End-to-end DL photonic-mmWave system
First page of the paper. Follow the DOI above for the published version.

Background

6G is moving toward the photonic-assisted mmWave regime, where dynamic spectrum allocation and multi-user transmission place stringent demands on the integrated communication system. End-to-end deep learning offers a way to jointly optimise across the cascaded fiber + mmWave link, but architectures that explicitly handle multi-user spectrum allocation are still missing.

Framework

We propose AMEF — Adaptive Multi-user End-to-end Framework — built from two parts: a Multi-Channel Model (MCM) that captures the cascaded photonic-assisted fiber + mmWave link, and a Multi-User Transceiver (MUT) consisting of a Multi-User Encoder (MUE) and a Multi-User Decoder (MUD), realized as MLP-based autoencoders that learn modulation, channel inversion and user separation jointly.

Highlights

  • Two-user 10 km fiber–mmWave experiment: 66 Gbps wireless and 49.5 Gbps fiber-wireless integrated
  • 1.1 dB / >0.6 dB receiver-sensitivity gain over mCAP modulation in the two systems" data-zh="相比 mCAP 调制，两套系统接收灵敏度分别提升 >1.1 dB / >0.6 dB">>1.1 dB / >0.6 dB receiver-sensitivity gain over mCAP modulation in the two systems
  • Joint learning of modulation, channel inversion and multi-user separation in one MLP autoencoder pipeline

Citation

A. Sun et al., "End-to-end deep-learning-based photonic-assisted multi-user fiber–mmWave integrated communication system," J. Lightwave Technology, 42(1), 2024.